Multi-Scale Transformer Encoder for Di-Tau Invariant Mass Reconstruction at CMS

A transformer-based encoder is proposed for the offline reconstruction of tau-lepton decays, with the goal of improving the estimation of the di-tau invariant mass. The model performs a regression of the transverse momentum of each tau candidate to recover the contribution carried away by neutrinos in the decay, while keeping and fixed in accordance with the collinear approximation valid in the targeted phase space. The self-attention mechanism enables the network to combine information from the visible decay products together with event-level observables when inferring the tau kinematics. The performance is evaluated on samples with di-tau final states from Standard Model and beyond-the-Standard-Model processes and compared with the FastMTT algorithm, commonly used as a reference for di-tau mass reconstruction. The transformer-based method shows potential as an alternative technique for offline di-tau mass reconstruction at the CMS experiment.